West China Hospital Endocrinology and Metabolism Department, West China School of Nursing, Sichuan University, Chengdu 610041, China.
West China School of Nursing, West China Hospital Endocrinology and Metabolism Department, Sichuan University, Chengdu 610041, China.
J Diabetes Res. 2023 Feb 16;2023:1199885. doi: 10.1155/2023/1199885. eCollection 2023.
The current study analyzed the status and the factors of foot ulcers in diabetic patients and developed a nomogram and web calculator for the risk prediction model of diabetic foot ulcers.
This was a prospective cohort study that used cluster sampling to enroll diabetic patients in the Department of Endocrinology and Metabolism in a tertiary hospital in Chengdu from July 2015 to February 2020. The risk factors for diabetic foot ulcers were obtained by logistic regression analysis. Nomogram and web calculator for the risk prediction model were constructed by R software.
The incidence of foot ulcers was 12.4% (302/2432). Logistic stepwise regression analysis showed that BMI (OR: 1.059; 95% CI 1.021-1.099), abnormal foot skin color (OR: 1.450; 95% CI 1.011-2.080), foot arterial pulse (OR: 1.488; 95% CI: 1.242-1.778), callus (OR: 2.924; 95%: CI 2.133-4.001), and history of ulcer (OR: 3.648; 95% CI: 2.133-5.191) were risk factors for foot ulcers. The nomogram and web calculator model were developed according to risk predictors. The performance of the model was tested, and the testing data were as follows: AUC (area under curve) of the primary cohort was 0.741 (95% CI: 0.7022-0.7799), and AUC of the validation cohort was 0.787 (95% CI: 0.7342-0.8407); the Brier score of the primary cohort was 0.098, and the Brier score of the validation cohort was 0.087.
The incidence of diabetic foot ulcers was high, especially in diabetic patients with a history of foot ulcers. This study presented a nomogram and web calculator that incorporates BMI, abnormal foot skin color, foot arterial pulse, callus, and history of foot ulcers, which can be conveniently used to facilitate the individualized prediction of diabetic foot ulcers.
本研究分析了糖尿病患者足部溃疡的现状和影响因素,并建立了预测糖尿病足溃疡风险的列线图和网络计算器。
本研究采用前瞻性队列研究,于 2015 年 7 月至 2020 年 2 月期间采用聚类抽样的方法,选取在成都某三甲医院内分泌代谢科就诊的糖尿病患者。采用 logistic 逐步回归分析获得糖尿病足溃疡的危险因素。利用 R 软件构建风险预测模型的列线图和网络计算器。
共纳入 2432 例糖尿病患者,其中 302 例(12.4%)发生足部溃疡。logistic 逐步回归分析显示,BMI(OR:1.059;95%CI 1.021-1.099)、足部皮肤颜色异常(OR:1.450;95%CI 1.011-2.080)、足部动脉脉搏(OR:1.488;95%CI:1.242-1.778)、胼胝(OR:2.924;95%CI:2.133-4.001)、溃疡史(OR:3.648;95%CI:2.133-5.191)是足部溃疡的危险因素。根据风险预测因素建立了列线图和网络计算器模型。对模型进行测试,检测数据如下:初级队列的 AUC(曲线下面积)为 0.741(95%CI:0.7022-0.7799),验证队列的 AUC 为 0.787(95%CI:0.7342-0.8407);初级队列的 Brier 评分 0.098,验证队列的 Brier 评分 0.087。
糖尿病患者足部溃疡的发生率较高,尤其是有足部溃疡史的患者。本研究建立了一种列线图和网络计算器,包含 BMI、足部皮肤颜色异常、足部动脉脉搏、胼胝和足部溃疡史,可方便地用于预测糖尿病患者的足部溃疡。